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Technical Debt Audit

Name: Technical Debt Audit
Author: 1kalin

作者 1kalin · GitHub ↗ · v1.0.0

cross-platform ✓ 安全检测通过

677

总下载

当前安装

版本数

在 OpenClaw 中安装

/install afrexai-tech-debt-audit

功能描述

Systematically identifies, scores, and prioritizes technical debt across codebases with impact analysis and detailed remediation roadmaps for engineering teams.

使用说明 (SKILL.md)

Technical Debt Audit

Systematic technical debt assessment for engineering teams. Identifies, scores, and prioritizes debt across your codebase with business impact analysis and remediation roadmaps.

What It Does

Debt Discovery — Categorizes debt: architecture, code quality, dependency, testing, infrastructure, documentation
Impact Scoring — Rates each item on effort (1-5), risk (1-5), and business impact (1-5) using a weighted formula
Cost Modeling — Estimates carrying cost per sprint in developer-hours and dollars
Remediation Roadmap — Generates a prioritized paydown plan with quick wins, scheduled work, and strategic rewrites
Executive Summary — One-page board-ready report showing debt-to-velocity ratio and projected savings

Usage

Describe your system, stack, and known pain points. The agent audits systematically:

"Audit our technical debt. We're a Node.js/React SaaS with 180K LOC, 
12 engineers. Known issues: monolithic API, no integration tests, 
3 deprecated dependencies, manual deployments."

Scoring Formula

Priority Score = (Risk × 3) + (Business Impact × 2) + (1/Effort × 1)

Higher score = fix first. Quick wins (low effort, high risk) surface to the top.

Debt Categories

Category	Examples	Typical Carrying Cost
Architecture	Monoliths, tight coupling, wrong patterns	15-25% velocity drag
Code Quality	Duplication, god classes, no standards	10-20% velocity drag
Dependencies	Outdated libs, security vulns, EOL frameworks	5-15% + incident risk
Testing	No tests, flaky tests, manual QA only	20-40% bug-fix overhead
Infrastructure	Manual deploys, no monitoring, snowflake servers	10-30% ops overhead
Documentation	No onboarding docs, tribal knowledge	2-4 weeks per new hire

Output Format

# Technical Debt Audit Report
## Executive Summary
- Total debt items: [N]
- Estimated carrying cost: $[X]/month
- Debt-to-velocity ratio: [X]%
- Quick wins available: [N] items, [X] dev-days

## Critical (Fix This Sprint)
...

## High Priority (Next 30 Days)  
...

## Scheduled (Next Quarter)
...

## Strategic (Plan & Budget)
...

## Remediation Roadmap
Week 1-2: [Quick wins]
Month 1: [High priority]
Quarter: [Scheduled items]

Why This Matters

Engineering teams spend 23-42% of development time on technical debt (Stripe Developer Report). Most don't measure it. What you don't measure, you can't manage.

Built by AfrexAI — AI-powered business operations tools.

Need the full engineering context pack? Browse our AI Context Packs ($47) or try the free AI Revenue Calculator.

安全使用建议

This skill is an instruction-only audit template and appears coherent with its purpose. Before using it: (1) confirm the source if you care about provenance (homepage/source are absent), (2) never paste API keys, private repo URLs, secrets, or full configuration files into the chat — provide high-level descriptions or sanitized examples instead, (3) test outputs on non-production data, and (4) if you want reduced risk, disable autonomous invocation for the agent or only invoke the skill interactively so you can vet any requests it makes.

功能分析

Type: OpenClaw Skill Name: afrexai-tech-debt-audit Version: 1.0.0 The skill bundle describes a 'Technical Debt Audit' functionality. All files (`_meta.json`, `SKILL.md`, `README.md`) consistently outline the purpose, features, and usage of this audit. There are no instructions for the AI agent to perform unauthorized actions, access sensitive data, execute external commands, or engage in any form of prompt injection. The external links provided are informational and promotional, not part of any malicious execution or exfiltration attempt. The content is entirely aligned with a benign, analytical tool.

能力评估

✓ Purpose & Capability

Name/README/SKILL.md describe a technical-debt audit tool and the skill's requirements (none) match that purpose. There are no unexpected requested credentials, binaries, or config paths that would be disproportionate for an audit guide.

ℹ Instruction Scope

SKILL.md is an instruction-only guide that asks the user to describe their system and pain points (expected). It does not instruct the agent to read files, access env vars, or call external endpoints. Note: the audit relies on user-supplied context, so users should avoid pasting secrets or sensitive configuration.

✓ Install Mechanism

No install spec and no code files — lowest risk. Nothing is downloaded or written to disk by the skill itself.

✓ Credentials

The skill requires no environment variables, credentials, or config paths. There are no disproportionate secret requests relative to the skill's function.

✓ Persistence & Privilege

always:false and default model invocation settings. The skill does not request permanent presence or elevated system privileges.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install afrexai-tech-debt-audit
安装完成后，直接呼叫该 Skill 的名称或使用 /afrexai-tech-debt-audit 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

Technical Debt Audit skill initial release: - Systematically discovers and categorizes technical debt across six key areas (architecture, code quality, dependencies, testing, infrastructure, documentation). - Scores each debt item by effort, risk, and business impact using a transparent weighted formula. - Estimates ongoing costs of technical debt in developer-hours and dollars per sprint. - Generates a prioritized remediation roadmap, highlighting quick wins, scheduled work, and strategic rewrites. - Produces an executive summary with debt-to-velocity ratio and projected savings for leadership.

元数据

Slug afrexai-tech-debt-audit

版本 1.0.0

许可证 —

累计安装 0

当前安装数 0

历史版本数 1

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